The source medical images undergo a three level fusion process. Two different fusion rules based on phase congruency and directive contrast are proposed and used to fuse lowand high-frequency coefficients. Finally, the fused image is subjected to another combined fusion using Centralization Method. | ISSN:2249-5789 Sinija T S et al, International Journal of Computer Science & Communication Networks,Vol 5(4),262-266 THREE LEVEL MULTIMODAL MEDICAL IMAGE FUSION MTECH, Department of computer science Assistant professor in CSE Mohandas College of Engineering Mohandas College of Engineering sinija33@ karthikcpta@ Abstract---The importance of information offered by the medical images for diagnosis support can be increased by combining images from different compactable medical devices. Medical image fusion has been used to derive useful information from multimodality medical image data. Fused image will be represented in format capable for computer processing. The source medical images undergo a three level fusion process. Two different fusion rules based on phase congruency and directive contrast are proposed and used to fuse lowand high-frequency coefficients. Finally, the fused image is subjected to another combined fusion using Centralization Method. Experimental results and comparative study show that the proposed fusion framework provides an effective way to enable more accurate analysis of multimodality images. Further, the applicability of the proposed framework is carried out by the three clinical examples of persons affected with Alzheimer, subacute stroke and recurrent tumor. resolution. As a result, the anatomical and functional medical images are needed to be combined for a compendious view. For this purpose, the multimodal medical image fusion has been identified as solution which aims to integrating information from multiple modality images to obtain a more complete and accurate description of the same object. Multimodal medical image fusion not only helps in diagnosing diseases, but it also reduces the storage cost by reducing storage to a single fused image instead of multiple-source images. The technique for medical image fusion have been categorized into three categories according to merging stage. .
